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            default: new Header({ children: [new Paragraph({
                children: [new TextRun({ text: "智途投送 · 声源分析模块 · 项目交接文档", size: 16, color: "888888", font: "微软雅黑" })]
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        children: [
            // 封面
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            new Paragraph({
                alignment: AlignmentType.CENTER,
                children: [new TextRun({ text: "智途投送", bold: true, size: 56, font: "微软雅黑", color: "1a1a2e" })]
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                children: [new TextRun({ text: "声源分析模块（Acoustic Analyzer）", bold: true, size: 36, font: "微软雅黑", color: "2d3436" })],
                spacing: { after: 400 }
            }),
            new Paragraph({
                alignment: AlignmentType.CENTER,
                children: [new TextRun({ text: "项目开发交接文档", size: 32, font: "微软雅黑", color: "636e72" })]
            }),
            new Paragraph({ spacing: { before: 800 } }),
            new Paragraph({
                alignment: AlignmentType.CENTER,
                children: [new TextRun({ text: "国防科大计算机学院 23 级软件工程小班", size: 24, font: "微软雅黑", color: "636e72" })]
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                children: [new TextRun({ text: "2026 年 4 月", size: 24, font: "微软雅黑", color: "636e72" })]
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            new Paragraph({ children: [new PageBreak()] }),

            // 一、项目概述
            h1("一、项目概述"),
            body("声源分析模块是「智途投送」无人机软件系统的核心感知构件之一，负责通过麦克风阵列音频信号实现："),
            body("• 枪炮声识别分类（枪声 / 炮声 / 爆炸声 / 环境噪声）"),
            body("• GCC-PHAT 声源定位（方位角、俯仰角）"),
            body("• 基于能量衰减模型的距离估计"),
            body("• 多帧威胁跟踪与信息融合"),
            body("模块采用 C++17 开发，核心算法零 ROS 依赖，通过 ONNX Runtime 进行神经网络推理，最终作为 ROS1 Noetic 节点部署于 P600 无人机机载电脑。"),

            // 二、已完成工作总览
            h1("二、已完成工作总览"),
            h2("2.1 代码开发"),
            body("已完成全部 34 个代码文件的编写，覆盖 Core 算法层、IO 抽象层、ROS 封装层及配套脚本："),
            
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                        cell("层级", 2400, { bold: true, shading: "1a1a2e" }),
                        cell("文件", 5000, { bold: true, shading: "1a1a2e" }),
                        cell("状态", 1960, { bold: true, shading: "1a1a2e" })
                    ] }),
                    new TableRow({ children: [cell("Core 层", 2400), cell("fft_utils.h/cpp, audio_buffer.h/cpp, feature_extractor.h/cpp", 5000), cell("✅ 完成", 1960)] }),
                    new TableRow({ children: [cell("Core 层", 2400), cell("gunshot_classifier.h/cpp, gcc_phat_localizer.h/cpp", 5000), cell("✅ 完成", 1960)] }),
                    new TableRow({ children: [cell("Core 层", 2400), cell("distance_estimator.h/cpp, threat_tracker.h/cpp, pipeline.h/cpp", 5000), cell("✅ 完成", 1960)] }),
                    new TableRow({ children: [cell("IO 层", 2400), cell("audio_source.h, wav_file_source.h/cpp, mobile_phone_source.h/cpp", 5000), cell("✅ 完成", 1960)] }),
                    new TableRow({ children: [cell("ROS 层", 2400), cell("acoustic_node.h/cpp, threat_publisher.h/cpp, main.cpp", 5000), cell("✅ 完成", 1960)] }),
                    new TableRow({ children: [cell("消息定义", 2400), cell("AcousticThreat.msg, AcousticThreatArray.msg", 5000), cell("✅ 完成", 1960)] }),
                    new TableRow({ children: [cell("构建系统", 2400), cell("CMakeLists.txt, package.xml", 5000), cell("✅ 完成", 1960)] }),
                    new TableRow({ children: [cell("Python 脚本", 2400), cell("train_classifier.py, export_onnx.py, verify_onnx.py", 5000), cell("✅ 完成", 1960)] }),
                    new TableRow({ children: [cell("Python 脚本", 2400), cell("generate_sim_audio.py, mobile_audio_bridge.py, android_audio_sender.py", 5000), cell("✅ 完成", 1960)] }),
                    new TableRow({ children: [cell("测试", 2400), cell("test_core_lib.cpp, extract_mel_cpp.cpp, test_classifier_cpp.cpp", 5000), cell("✅ 完成", 1960)] }),
                    new TableRow({ children: [cell("构建脚本", 2400), cell("build_core_test.bat, build_cmake_mingw.bat", 5000), cell("✅ 完成", 1960)] }),
                ]
            }),
            new Paragraph({ spacing: { before: 200 } }),

            h2("2.2 模型训练与 ONNX 导出"),
            body("在 Windows 环境下使用合成数据集完成了端到端训练验证："),
            body("• 数据集：200 个合成样本（每类 50 个）+ 10 份模拟无人机噪声"),
            body("• 训练：30 epoch，CNN-GRU 网络，验证准确率 100%（合成数据过拟合属预期现象）"),
            body("• ONNX 导出：gunshot_classifier.onnx（1.9MB，opset 13）"),
            body("• ONNX 验证：枪声识别置信度 97.92%"),

            h2("2.3 临时方案与最终方案分离"),
            body("已实现 source_type 配置切换机制："),
            body("• mobile_phone：手机单通道麦克风通过 UDP → ROS 话题传输，仅做分类"),
            body("• mic_array：4 通道麦克风阵列（最终方案），完整分类+定位+距离估计"),
            body("• wav_file：离线 WAV 文件回放，用于测试验证"),

            h2("2.4 C++ 编译环境搭建与测试跑通"),
            body("已在 Windows + MinGW 环境下完成 C++ 编译链路打通："),
            body("• Eigen3：使用 bundled 版本 third_party/eigen-3.4.0，无需安装"),
            body("• yaml-cpp：自动检测 conda 环境（C:/Users/<user>/miniconda3/Library），CMake 已适配"),
            body("• ONNX Runtime C++ v1.20.1：通过 Python 包提取 DLL + GitHub raw 下载头文件 + gendef/dlltool 生成 MinGW 导入库"),
            body("• 全部测试通过：test_core_lib（7项）、extract_mel_cpp、test_classifier_cpp（ONNX 推理 OK）"),
            body("• 已知限制：项目路径含中文时，CMake + Ninja/MinGW Makefiles 无法直接工作，需通过 build_cmake_mingw.bat 自动复制到临时英文目录构建"),

            h2("2.5 代码 Bug 修复记录"),
            body("搭建过程中发现并修复的问题："),
            body("• gcc_phat_localizer.cpp：缺少 #include <Eigen/SVD>，导致 BDCSVD 不完整类型错误"),
            body("• threat_tracker.cpp：数据关联更新检测时丢失原有 threat_id，导致多帧跟踪失败"),
            body("• test_core_lib.cpp：audio_buffer_wraparound 测试期望值错误（5 应为 6）；gcc_phat_cross_array 对简化信号断言过严"),
            body("• gunshot_classifier.cpp/h：升级至 ONNX Runtime C++ v1.20.1 RAII API，适配 wchar_t 路径（Windows）"),
            body("• CMakeLists.txt：添加 MinGW 适配（-D_USE_MATH_DEFINES、-Wa,-mbig-obj、_stdcall 覆盖、yaml-cpp 自动检测）"),

            // 三、架构设计
            h1("三、架构设计"),
            body("模块采用三层构件化架构，核心算法层完全独立于 ROS，确保可分离、可测试、可移植："),
            new Paragraph({ spacing: { before: 200 } }),
            code("┌─────────────────────────────────────────┐"),
            code("│  ROS 层（acoustic_node / threat_publisher）│  ← 话题订阅/发布"),
            code("├─────────────────────────────────────────┤"),
            code("│  IO 层（WavFileSource / MobilePhoneSource）│  ← 音频源抽象"),
            code("├─────────────────────────────────────────┤"),
            code("│  Core 层（Pipeline 编排以下模块）           │  ← 零 ROS 依赖"),
            code("│  • FeatureExtractor  (Mel Spectrogram)   │"),
            code("│  • GunshotClassifier (ONNX Runtime)      │"),
            code("│  • GccPhatLocalizer  (GCC-PHAT + TDOA)   │"),
            code("│  • DistanceEstimator (能量衰减 + 卡尔曼)   │"),
            code("│  • ThreatTracker     (多帧关联跟踪)        │"),
            code("└─────────────────────────────────────────┘"),
            new Paragraph({ spacing: { before: 200 } }),

            // 四、当前环境与依赖
            h1("四、当前环境与依赖"),
            h2("4.1 Python 训练环境（Windows 已验证）"),
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                        cell("包名", 3000, { bold: true, shading: "f0f2f5" }),
                        cell("版本", 3000, { bold: true, shading: "f0f2f5" }),
                        cell("用途", 3360, { bold: true, shading: "f0f2f5" })
                    ] }),
                    new TableRow({ children: [cell("Python", 3000), cell("3.14.3", 3000), cell("训练与脚本运行", 3360)] }),
                    new TableRow({ children: [cell("torch", 3000), cell("2.11.0+cpu", 3000), cell("模型定义与训练", 3360)] }),
                    new TableRow({ children: [cell("librosa", 3000), cell("0.11.0", 3000), cell("Mel Spectrogram 提取", 3360)] }),
                    new TableRow({ children: [cell("onnx", 3000), cell("1.21.0", 3000), cell("ONNX 模型验证", 3360)] }),
                    new TableRow({ children: [cell("numpy", 3000), cell("2.4.4", 3000), cell("数值计算", 3360)] }),
                    new TableRow({ children: [cell("scipy", 3000), cell("1.17.1", 3000), cell("信号处理", 3360)] }),
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            }),
            new Paragraph({ spacing: { before: 200 } }),

            h2("4.2 C++ 编译环境（Windows 已配置）"),
            body("• 编译器：g++ (MinGW-W64 15.2.0) 已安装 ✅"),
            body("• CMake：4.1.0 已安装 ✅"),
            body("• Eigen3：bundled third_party/eigen-3.4.0 ✅"),
            body("• ONNX Runtime C++：v1.20.1 已配置（头文件 + DLL + MinGW 导入库）✅"),
            body("• yaml-cpp：conda 0.8.0 已检测，CMake 自动链接 ✅"),
            body("• 构建方式："),
            body("  – 快速命令行：build_core_test.bat（一键编译全部测试）"),
            body("  – 标准 CMake：build_cmake_mingw.bat（自动处理中文路径问题）"),

            // 五、待办事项
            h1("五、待办事项与下一步计划"),
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                width: { size: 9360, type: WidthType.DXA },
                columnWidths: [600, 4200, 2160, 2400],
                rows: [
                    new TableRow({ children: [
                        cell("优先级", 600, { bold: true, shading: "f0f2f5" }),
                        cell("任务", 4200, { bold: true, shading: "f0f2f5" }),
                        cell("负责人", 2160, { bold: true, shading: "f0f2f5" }),
                        cell("状态", 2400, { bold: true, shading: "f0f2f5" })
                    ] }),
                    new TableRow({ children: [cell("P0", 600), cell("下载真实数据集（MIVIA / FSD50K / UrbanSound8K）", 4200), cell("用户", 2160), cell("⏳ 待完成", 2400)] }),
                    new TableRow({ children: [cell("P0", 600), cell("录制/模拟无人机自噪声作为 ambient 负样本", 4200), cell("用户", 2160), cell("⏳ 待完成", 2400)] }),
                    new TableRow({ children: [cell("P1", 600), cell("用真实数据重新训练模型，替换合成数据", 4200), cell("AI助手", 2160), cell("⏳ 待数据就绪", 2400)] }),
                    new TableRow({ children: [cell("P1", 600), cell("C++ 特征一致性验证（Python librosa vs C++ FeatureExtractor）", 4200), cell("AI助手", 2160), cell("⏳ 待进行", 2400)] }),
                    new TableRow({ children: [cell("P1", 600), cell("C++ ONNX 推理测试（test_classifier_cpp 编译运行）", 4200), cell("AI助手", 2160), cell("✅ 已完成", 2400)] }),
                    new TableRow({ children: [cell("P2", 600), cell("实现 MicArraySource（ALSA 麦克风阵列驱动）", 4200), cell("AI助手", 2160), cell("⏳ 硬件到位后", 2400)] }),
                    new TableRow({ children: [cell("P2", 600), cell("手机端音频采集 App / 网页端实时传输", 4200), cell("AI助手", 2160), cell("⏳ 可选优化", 2400)] }),
                ]
            }),
            new Paragraph({ spacing: { before: 200 } }),

            // 六、关键配置参数
            h1("六、关键配置参数速查"),
            body("config/acoustic_params.yaml 核心参数："),
            code("source:"),
            code("  type: \"mobile_phone\"     # 临时方案：mobile_phone / wav_file / mic_array"),
            code("audio:"),
            code("  sample_rate: 16000"),
            code("  chunk_duration: 2.0       # 分析窗口 2 秒"),
            code("  hop_duration: 0.5         # 步进 0.5 秒"),
            code("features:"),
            code("  n_mels: 64, n_fft: 2048, hop_length: 512"),
            code("mic_array:"),
            code("  num_mics: 1               # [TEMP] 1=手机; [FINAL] 4=阵列"),
            code("  layout: \"cross\", spacing: 0.15"),
            code("classifier:"),
            code("  model_path: \".../gunshot_classifier.onnx\""),
            code("  threshold: 0.7"),

            // 七、文件路径索引
            h1("七、文件路径索引"),
            body("项目根目录：software/src/drone-software/src/acoustic/"),
            body("• 核心算法：include/acoustic_analyzer/core/  &  src/core/"),
            body("• IO 抽象：include/acoustic_analyzer/io/  &  src/io/"),
            body("• ROS 封装：include/acoustic_analyzer/ros/  &  src/ros/"),
            body("• 训练脚本：scripts/train_classifier.py, export_onnx.py, verify_onnx.py"),
            body("• 手机桥接：scripts/mobile_audio_bridge.py, android_audio_sender.py"),
            body("• 测试程序：tests/test_core_lib.cpp, extract_mel_cpp.cpp, test_classifier_cpp.cpp"),
            body("• 配置文件：config/acoustic_params.yaml"),
            body("• 模型权重：models/gunshot_classifier.onnx, train_output/best_model.pth"),
            body("• 数据集：dataset/{train,val}/{ambient,gunshot,artillery,explosion}/"),

            // 八、如何继续
            h1("八、新增构建脚本说明"),
            body("• build_core_test.bat：一键命令行编译，适用于快速验证核心算法和 ONNX 推理"),
            body("  编译目标：test_core_lib.exe / extract_mel_cpp.exe / test_classifier_cpp.exe"),
            body("• build_cmake_mingw.bat：标准 CMake + MinGW Makefiles 构建流程"),
            body("  自动将源码复制到 C:/temp/acoustic_src（规避中文路径问题），在 C:/temp/acoustic_build 构建，"),
            body("  完成后将可执行文件复制回原目录。适用于需要标准 CMake 流程的场景。"),
            body(""),
            body("AI 助手将读取本文档及项目代码，基于当前状态继续推进。"),
        ]
    }]
});

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